var fs = require('fs')
  , test = require('tape')
  , cv = null



test("Smoke tests / Can Import", function(t){
  cv = require('../lib/opencv')
  t.ok(cv, "imported fine")
  t.ok(cv.version, "version is there:" + cv.version)
  t.ok(cv.Point, "point is there")
  t.ok(cv.Matrix, "matrix is there")
  t.end()
})


test('importing library multiple times is ok', function(t){
  var cv1 = require('../lib/opencv')
    , cv2 = require('../lib/opencv')
    cv1.readImage('./examples/files/mona.png', function(err, im){
      t.error(err)
      cv2.readImage('./examples/files/mona.png', function(err, im){
        t.error(err)
        t.end();
      });
    });
})


test('Point', function(t){

  t.ok(new cv.Point(1, 2))
  t.throws(function () { cv.Point(1, 2)}, TypeError, "cannot call without new")

  t.equal(new cv.Point(1, 2).x, 1)
  t.equal(new cv.Point(1, 2).y, 2)
  t.equal(Math.round(new cv.Point(1.1, 2).x * 100), 110)
  t.equal(Math.round(new cv.Point(1.2, 2.75).y *100), 275)

  t.throws(function () {new cv.Point(1.1, 2).x = 5}, Error, "Points are immutable")
  t.throws(function () {new cv.Point(1.1, 2).y = 5}, Error, "Points are immutable")

  var p1 = new cv.Point(3, 6)
    , p2 = new cv.Point(5, 7)

  t.ok(p1.dot);
  t.equal(p1.dot(p2), 57);

  t.end()
})


test('Matrix constructor', function(assert){
  assert.ok(cv.Matrix);
  assert.ok(new cv.Matrix);
  assert.ok(new cv.Matrix(1, 2));
  assert.ok(new cv.Matrix(1, 2, cv.Constants.CV_8U));
  assert.ok(new cv.Matrix(1, 2, cv.Constants.CV_8U, [1]));
  assert.end()
})

test('Matrix accessors', function(assert){
  var mat = new cv.Matrix(1, 2);
  mat.set(0,0,3);
  mat.set(0,1,5000);
  assert.deepEqual(mat.row(0), [3,5000]);

  mat = new cv.Matrix(1,2);
  assert.equal(mat.set(0,0,3), undefined);
  assert.equal(mat.get(0,0), 3);

  mat = new cv.Matrix(6,7);
  assert.equal(mat.width(), 7);

  mat = new cv.Matrix(6,7);
  assert.equal(mat.height(), 6);

  mat = new cv.Matrix(6,7);
  assert.deepEqual(mat.size(), [6, 7]);

  mat = new cv.Matrix(6,7);
  assert.equal(mat.width(), 7);
  mat.resize(8,9);
  assert.equal(mat.width(), 8);

  mat = new cv.Matrix.Eye(4,4)
  assert.deepEqual(mat.row(1), [0,1,0,0])
  assert.deepEqual(mat.row(2), [0,0,1,0])

  mat = new cv.Matrix.Eye(4,4);
  assert.deepEqual(mat.col(1), [0,1,0,0])
  assert.deepEqual(mat.col(2), [0,0,1,0])

  assert.equal(new cv.Matrix().empty(), true);

  mat = new cv.Matrix(1, 2, cv.Constants.CV_8UC3, [1, 2, 3]);
  assert.deepEqual(mat.pixelRow(0), [1, 2, 3, 1, 2, 3]);

  assert.end()
})

test('Matrix functions', function(assert) {
  // convertTo
  var mat = new cv.Matrix(75, 75, cv.Constants.CV_32F, [2.0]);
  var matNew = new cv.Matrix(75, 75, cv.Constants.CV_8U);
  var alpha = 2;
  var beta = 1;
  mat.convertTo(matNew, cv.Constants.CV_8U, alpha, beta);
  assert.equal(matNew.pixel(0, 0), mat.get(0, 0)*alpha + beta);

  // reshape
  mat = new cv.Matrix(75, 75, cv.Constants.CV_8UC1);
  matNew = mat.reshape(1, 1);
  assert.equal(matNew.height(), 1);
  assert.equal(matNew.width(), 5625);

  // GetRotationMatrix2D
  mat = cv.Matrix.getRotationMatrix2D(0, 0, 90, 1.0);
  assert.deepEqual(mat.size(), [2,3], 'GetRotationMatrix2D');

  assert.end();
})

test(".norm", function(assert){
  cv.readImage("./examples/files/coin1.jpg", function(err, im) {
    cv.readImage("./examples/files/coin2.jpg", function(err, im2){
      assert.ok(im);
      assert.ok(im2);

      var errorL2 = im.norm(im2, cv.Constants.NORM_L2);
      assert.equal(errorL2, 7295.591339980605);
      errorL2 = im.norm(im, cv.Constants.NORM_L2);
      assert.equal(errorL2, 0);
      assert.end();
    });
  });
})

test("Matrix toBuffer", function(assert){
  var buf = fs.readFileSync('./examples/files/mona.png')

  cv.readImage(buf.slice(0), function(err, mat){
    var buf0 = mat.toBuffer()
    assert.ok(buf0);
    assert.end()
  })
})

test("Matrix toBuffer Async", function(assert){
  var buf = fs.readFileSync('./examples/files/mona.png')

  cv.readImage(buf.slice(0), function(err, mat){
    mat.toBuffer(function(err, buff){
      assert.error(err)
      assert.ok(buf)
      assert.ok(buf.length > 100)

      assert.end()
    })
  })
})


test("detectObject", function(assert){
  cv.readImage("./examples/files/mona.png", function(err, im){
    im.detectObject(cv.FACE_CASCADE, {}, function(err, faces){
      assert.error(err)
      assert.ok(faces)
      assert.equal(faces.length, 1)
      assert.end()
    })
  })
})

test(".absDiff and .countNonZero", function(assert){
  cv.readImage("./examples/files/mona.png", function(err, im) {
    cv.readImage("./examples/files/mona.png", function(err, im2){
      assert.ok(im);
      assert.ok(im2);

      var diff = new cv.Matrix(im.width(), im.height());
      diff.absDiff(im, im2);

      diff.convertGrayscale();
      assert.equal(diff.countNonZero(), 0);
      assert.end()
    });
  });
})


test(".bitwiseXor", function(assert){
  var mat1 = new cv.Matrix(1,1);
  mat1.set(0,0, 1);

  var mat2 = new cv.Matrix(1,1);
  mat2.set(0,0, 1);

  var xored = new cv.Matrix(1,1);
  xored.bitwiseXor(mat1, mat2);

  assert.equal(xored.get(0,0), 0);

  assert.end()
})


test("Image read from file", function(assert){
  cv.readImage("./examples/files/opencv.png", function(err, im){
    assert.ok(im);
    assert.equal(im.width(), 82);
    assert.equal(im.height(), 99);
    assert.equal(im.channels(), 4);
    assert.equal(im.empty(), false);
    assert.end();
  })
})

test("Multi-page image read from file", function(assert){
  if (parseInt(cv.version) >= 3) {
    cv.readImageMulti("./examples/files/multipage.tif", function(err, imgs){
      assert.ok(imgs);
      assert.equal(imgs.length, 10);
      for (var i = 0; i < imgs.length; i++) {
        assert.ok(imgs[i]);
        assert.equal(imgs[i].width(), 800);
        assert.equal(imgs[i].height(), 600);
        assert.equal(imgs[i].channels(), 3);
        assert.equal(imgs[i].empty(), false);
      }
      assert.end();
    })
  } else {
    assert.equal(cv.readImageMulti("./examples/files/multipage.tif"), false);
    assert.end();
  }
})

test("Distance transform", function(assert){
  cv.readImage("./examples/files/distanceTransform.png", function(err, img){
    assert.ok(img);

    // 50px image with single black pixel on right side
    var result = cv.imgproc.distanceTransform(img, cv.Constants.CV_DIST_L2, cv.Constants.CV_DIST_MASK_PRECISE);
    assert.equal(result.get(0,0), 49);
    assert.end();
  })
})

test("read Image from buffer", function(assert){
  cv.readImage(fs.readFileSync('./examples/files/opencv.png'), function(err, im){
    assert.ok(im);
    assert.equal(im.width(), 82);
    assert.equal(im.height(), 99);
    assert.equal(im.channels(), 4);
    assert.equal(im.empty(), false);
    assert.end();
  })
})

test("Cascade Classifier", function(assert){
  assert.ok(new cv.CascadeClassifier("./data/haarcascade_frontalface_alt.xml"), 'test constructor')

  cv.readImage("./examples/files/mona.png", function(err, im){
    cascade = new cv.CascadeClassifier("./data/haarcascade_frontalface_alt.xml");
    cascade.detectMultiScale(im, function(err, faces){//, 1.1, 2, [30, 30]);
      assert.error(err);
      assert.equal(typeof faces, typeof []);
      assert.equal(faces.length, 1)
      assert.end()
    })
  })
})


test("ImageDataStream", function(assert){
  var s = new cv.ImageDataStream()
  s.on('load', function(im){
    assert.ok(im)
    assert.equal(im.empty(), false);
    assert.end()
  })

  fs.createReadStream('./examples/files/mona.png').pipe(s);

})

test("ImageStream", function(assert){
  var s = new cv.ImageStream()
    , im = fs.readFileSync('./examples/files/mona.png')

  s.on('data', function(mat){
    assert.deepEqual(mat.size(), [756,500])
    assert.end()
  })
  s.write(im);
})


test("CamShift", function(assert){
  cv.readImage('./examples/files/coin1.jpg', function(e, im){
    cv.readImage('./examples/files/coin2.jpg', function(e, im2){
      var tracked = new cv.TrackedObject(im, [420, 110, 490, 170], {channel: 'v'});
      assert.ok(tracked);
      var res = tracked.track(im2)
      assert.ok(res);
      assert.ok(res[0]  < 396)
      assert.ok(res[0]  > 376)
      assert.ok(res[1]  < 122)
      assert.ok(res[1]  > 102)
      assert.ok(res[2]  < 469)
      assert.ok(res[2]  > 449)
      assert.ok(res[3]  < 176)
      assert.ok(res[3]  > 156)
      assert.end()
    })
  })
})

test("fonts", function(t) {

  function rnd() {
    return Math.round(Math.random() * 255);
  };

  cv.readImage("./examples/files/coin1.jpg", function(e, im){
    var y = 0;
    var scale = 1;

    ([
      "HERSEY_SIMPLEX",
      "HERSEY_PLAIN",
      "HERSEY_DUPLEX",
      "HERSEY_COMPLEX",
      "HERSEY_TRIPLEX",
      "HERSEY_COMPLEX_SMALL",
      "HERSEY_SCRIPT_SIMPLEX",
      "HERSEY_SCRIPT_COMPLEX",
      "HERSEY_SCRIPT_SIMPLEX"
    ]).forEach(function(font) {
      im.putText("Some text", 0, y += 20, font, [rnd(), rnd(), rnd()], 2, scale++);
    });

    t.ok(im, "image is ok");
    im.save("./examples/tmp/coin1-with-text.jpg");
    t.end();
  });
})

test('LDA Wrap', function(assert) {
  if (cv.LDA === undefined) {
    console.log('TODO: Please port LDAWrap.cc to OpenCV 3')
    assert.end();
    return;
  }

  // subspaceProject
  var mat = cv.LDA.subspaceProject(new cv.Matrix(1, 2, cv.Constants.CV_64F), new cv.Matrix(), new cv.Matrix(2, 1, cv.Constants.CV_8UC1));
  assert.deepEqual(mat.size(), [2,2], 'subspaceProject');

  // subspaceReconstruct
  mat = cv.LDA.subspaceReconstruct(new cv.Matrix(1, 2, cv.Constants.CV_64F), new cv.Matrix(), new cv.Matrix(1, 2, cv.Constants.CV_8UC1));
  assert.deepEqual(mat.size(), [1,1], 'subspaceReconstruct');

  assert.end();
})


test('Native Matrix', function(assert) {
  var nativemat = require('../build/' + (!!process.env.NODE_OPENCV_DEBUG ? 'Debug' : 'Release') + '/test_nativemat.node');
  var mat = new cv.Matrix(42, 8);

  assert.deepEqual(mat.size(), nativemat.size(mat), 'nativemat');
  assert.end();
})

test('Subtract', function(assert) {
  var a = new cv.Matrix.Zeros(1,1);
  a.set(0, 0, 3);
  var b = new cv.Matrix.Zeros(1,1);
  b.set(0, 0, 1);
  a.subtract(b);
  assert.deepEqual(a.get(0, 0), 2);
  assert.end();
});

test('Mean', function(assert) {
  var a = new cv.Matrix.Zeros(2, 2, cv.Constants.CV_8UC3);

  // Set [0, 0] element to 1 for all three channels
  a.set(0, 0, 1, 0);
  a.set(0, 0, 1, 1);
  a.set(0, 0, 1, 2);

  var means = a.mean();
  assert.deepEqual(means, [0.25, 0.25, 0.25, 0]);
  assert.end();
});

test('Compare', function(assert) {
  var a = cv.Matrix.fromArray([[[0],[-20]],[[2],[-18]]], cv.Constants.CV_8SC1);
  var b = cv.Matrix.fromArray([[[3],[-20]],[[0],[-16]]], cv.Constants.CV_8SC1);

  var compare1 = a.compare(b, cv.Constants.CMP_EQ);
  var compare2 = a.compare(b, cv.Constants.CMP_GT);
  var compare3 = a.compare(b, cv.Constants.CMP_LE);

  assert.deepEqual(compare1.toArray(), [[[0],[255]],[[0],[0]]]);
  assert.deepEqual(compare2.toArray(), [[[0],[0]],[[255],[0]]]);
  assert.deepEqual(compare3.toArray(), [[[255],[255]],[[0],[255]]]);

  assert.end();
});

test('MatchTemplateByMatrix', function(assert) {
  var cv = require('../lib/opencv');
  var targetFilename = "./examples/files/car1.jpg";
  var templateFilename = "./examples/files/car1_template.jpg";
  cv.readImage(targetFilename, function(err, target){
    cv.readImage(templateFilename, function(err, template){
      var TM_CCORR_NORMED = 3;
      var res = target.matchTemplateByMatrix(template, TM_CCORR_NORMED);
      var minMax = res.minMaxLoc();
      var topLeft = minMax.maxLoc;
      assert.ok(topLeft, "RGB Found Match");
      assert.equal(topLeft.x, 42, "match location x === 42");
      assert.equal(topLeft.y, 263, "match location y === 263");
      target.canny(5,300);
      template.canny(5,300);
      res = target.matchTemplateByMatrix(template, TM_CCORR_NORMED);
      minMax = res.minMaxLoc();
      topLeft = minMax.maxLoc;
      assert.ok(topLeft, "Canny edge Found Match");
      assert.equal(topLeft.x, 42, "match location x === 42");
      assert.equal(topLeft.y, 263, "match location y === 263");
      assert.end();
    });
  })
});

test('setColor works will alpha channels', function(assert) {
  var cv = require('../lib/opencv');
  var mat = new cv.Matrix(100, 100, cv.Constants.CV_8UC4);

  var SQUARE = [ 50, 50 ];
  mat.rectangle([ 0, 0 ], SQUARE, [ 0, 187, 255, 255 ], -1);
  mat.rectangle([ 0, 50 ], SQUARE, [ 0, 187, 124, 200 ], -1);
  mat.rectangle([ 50, 0 ], SQUARE, [ 241, 161, 0, 128 ], -1);
  mat.rectangle([ 50, 50 ], SQUARE, [ 20, 83, 246, 70 ], -1);

  cv.readImage('./examples/files/alpha-test.png', function(err, imgMat) {
    if (!err) {
      var diff = new cv.Matrix();
      diff.absDiff(mat, imgMat);
      // We'll verify that each channel is 0
      var channels = diff.split();
      for (var i = 0; i < 4; i++) {
        assert.equal(channels[i].countNonZero(), 0);
      }
    } else {
      throw err;
    }
    assert.end();
  });
});

test('getPixel',function(assert){
  cv.readImage('./examples/files/alpha-test.png', function(err, imgMat) {
    if (!err) {
      assert.equal(imgMat.channels(),4);
      assert.deepEqual(imgMat.getPixel(10,10),[0,187,255,255]);
      assert.deepEqual(imgMat.getPixel(30,80),[241,161,0,128]);
      assert.deepEqual(imgMat.getPixel(80,30),[0,187,124,200]);
      assert.deepEqual(imgMat.getPixel(80,80),[20,83,246,70]);

      var channels = imgMat.split();
      imgMat.merge([channels[0],channels[1],channels[2]]);
      assert.equal(imgMat.channels(),3);
      assert.deepEqual(imgMat.getPixel(10,10),[0,187,255]);
      assert.deepEqual(imgMat.getPixel(30,80),[241,161,0]);
      assert.deepEqual(imgMat.getPixel(80,30),[0,187,124]);
      assert.deepEqual(imgMat.getPixel(80,80),[20,83,246]);

      imgMat.merge([channels[3]]);
      assert.equal(imgMat.channels(),1);
      assert.deepEqual(imgMat.getPixel(0,0),255);
      assert.deepEqual(imgMat.getPixel(30,80),128);
      assert.deepEqual(imgMat.getPixel(80,30),200);
      assert.deepEqual(imgMat.getPixel(80,80),70);

    } else {
      throw err;
    }
    assert.end();
  });
});

test('pixelRow pixelCol 4 channel image ',function(assert){
  cv.readImage('./examples/files/alpha-small.png', function(err, imgMat) {
    if (!err) {
      assert.equal(imgMat.channels(),4);

      assert.deepEqual(imgMat.pixelCol(0),
        [ 0, 0,   0, 255,
          0, 255, 0, 88,
          0, 0,   0, 88 ]);

      assert.deepEqual(imgMat.pixelCol(1),
        [ 255, 255, 255, 255,
          0,   0,   255, 88,
          255, 255, 255, 88 ]);

      assert.deepEqual(imgMat.pixelRow(0),
        [ 0,   0,   0,   255,
          255, 255, 255, 255,
          0,   255, 0,   255,
          255, 0,   0,   255,
          0,   0,   255, 255,
          229, 194, 201, 155 ]);

      assert.deepEqual(imgMat.pixelRow(1),
        [ 0,   255, 0,   88,
          0,   0,   255, 88,
          255, 0,   0,   88,
          47,  40,  42,  155,
          145, 66,  125, 227,
          47,  100, 163, 72 ]);
    } else {
      throw err;
    }
    assert.end();
  });
});


test('toArray/fromArray working in both ways', function(assert) {
  var cv = require('../lib/opencv');

  cv.readImage("./examples/files/mona.png", function(err, orig) {
    if (err) throw err;

    var a = orig.toArray();
    var type = orig.type();
    var doubleConversion = cv.Matrix.fromArray(a, type).toArray();

    var randomI = Math.floor(Math.random()*a.length)
    var randomJ = Math.floor(Math.random()*a[randomI].length)
    var randomK = Math.floor(Math.random()*a[randomI][randomJ].length)

    assert.equal(a[randomI][randomJ][randomK], doubleConversion[randomI][randomJ][randomK]);
    assert.end();
  });
});

// Test the examples folder.
require('./examples')()
